Remote monitoring of sleep activity in patients diagnosed with glioblastoma.
Authors: Brandon Noorvash, L J Amaral, Thomas Nelson, Jeremy David Rudnick, Scott A Irwin, Stephen J. Freedland, Gillian Gresham, Jethro Lisien Hu
Journal: Journal of Clinical Oncology (2022)

e14036 Background: Sleep disturbance is a common symptom experienced in patients diagnosed with glioblastoma (GBM) and has been correlated with poor physical and psychological outcomes. Advancements in wearable technologies have allowed for the opportunity to obtain objective measures of sleep quality outside of a laboratory setting. Thus, we conducted a secondary analysis of remotely monitored sleep data from a phase 1 study of newly diagnosed GBM patients following a classic ketogenic diet (KD) in addition to standard-of-care treatment. Methods: Patients with GBM were recruited between 04/2018-02/2021 to take part in a 16-week KD intervention with dietitian support. Patients’ physical activity (PA) (average step counts, duration of light/moderate/vigorous activity), nocturnal sleep data (total sleep time, restlessness and duration in light/deep/REM sleep), and sleep efficiency were collected through the use of a wearable activity monitor (Fitbit Charge HR3). Patient-reported quality of life (QoL) (QLQC30), PA, and sleep metrics were summarized at baseline, week 8, and week 16 (end of study). Correlation statistics were calculated between sleep measures, PA, and QoL outcomes. Results: Patients with available sleep data (n = 16) were included in the analysis (53% women, median age 55 years). Among the 16 included patients, adherence to wearing the device was 100% at baseline, 94% at 8 weeks, and 75% at week 16. Overall, mean sleep duration at baseline (days 1-7) was 6.5 hours (SD: 0.94) (n = 16), with an average sleep efficiency score of 92.9 (SD: 2.7), and an average number of sleep disturbances of 20.1 (SD: 6.7). Average duration in light, deep, and REM sleep (hours) was 4.6 (SD:0.98), 0.78 (SD:0.5), and 1.1 (SD:0.34), respectively. Longer baseline sleep duration was significantly correlated with daily step counts (correlation coefficient (r):0.55, p = 0.02), duration in PA (r: 0.55, p = 0.03), and improved QOL, although not statistically significant (r: 0.5, p = 0.06). Longer duration in REM sleep was also significantly correlated with higher patient-reported physical function (r: 0.64, p = 0.01), cognitive function (r: 0.61, p = 0.02), decreased fatigue (r: -0.67, p = 0.01), and increased duration in PA (r: 0.59, p = 0.01). Conclusions: Our findings suggest that it was feasible to remotely monitor sleep activity in this population. This cohort of GBM patients present with shorter sleep duration than the recommended 7 hours and as compared to adults living with cancer and other chronic disease. Significant correlations were observed between sleep outcomes, notably in regard to duration in REM sleep, PA levels, patient-reported physical and cognitive function and fatigue. The use of wearable technology can provide additional insight into a patient’s sleep patterns and inform the development of tailored interventions for sleep disturbances. Given the small sample size, further research is warranted to validate these findings. Clinical trial information: NCT03451799.